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ABSTRACT
Wireless Sensor Network (WSN) infrastructure has to be balanced for maintaining the Quality of Service (QoS) in the network. However, load balancing technology is complex for meeting the requirements of high flexibility and adaptability due to the conventional WSN architecture. The major complication for developing distributed techniques for these models is load balancing that is the major aim of this study. These distributed methodologies use routing decisions that must be efficient without the need for more information about the system, where one of the efficient techniques is probabilistic routing. This paper plans to conduct a critical literature review on a diverse centralised server for controlling the load balancing in the cloud and routing strategies in WSN as well as linked with an IoT systems. This study reviews a set of contributions regarding load balancing in the cloud and routing strategies in WSN with clear algorithmic analysis. The simulation tools and recorded performance measures are also analysed and sorted out. Finally, the existing research gaps and the future directions are expedited that to be adaptable to attain better protocol performance with a centralised server in balancing node traffic, load balancing in the cloud and improving the throughput of the entire network.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notation table
| Abbreviation | = | Description |
| ASLPR | = | Application Specific Low Power Routing |
| ACO | = | Ant Colony Algorithm |
| AMPL | = | A Modeling Language for Mathematical Programming |
| BFO | = | Bacteria Foraging Optimize |
| C2 | = | Cloud Cache |
| CARP | = | Channel-Aware Distributed Routing Protocol |
| DA | = | Dragonfly Algorithm |
| D2D | = | Device-to-Device |
| DWOLB | = | Dynamic Well-Organized Load Balancing |
| DMCQR | = | Deterministic Multi-Constrained Centralized QoS Routing |
| DLBS | = | Dynamical Load-Balanced Scheduling |
| E-ALWO | = | Exponentially-Ant Lion Whale Optimization |
| EEQR | = | Energy Efficient and QoS aware Routing |
| EERP | = | Energy-Efficient Routing Protocol |
| FA | = | Firefly Algorithm |
| FDLA | = | Fractional Dragonfly Based Load Balancing Algorithm |
| FC | = | Fractional Calculus |
| FLION | = | Fractional Lion clustering algorithm |
| FMCR-CT | = | Fuzzy Multi Cluster-Based Routing with a Constant Threshold |
| FPT | = | Fixed Parameter Tractable |
| FFO | = | Fruit Fly Optimisation |
| GWO | = | Grey Wolf Optimizer |
| GSO | = | Glowworm Swarm Optimisation |
| GA | = | Genetic Algorithm |
| GECR | = | GA-based Energy-efficient Clustering and Routing approach |
| HEFT | = | Hybrid Heterogeneous Earliest Finish Time |
| HHO | = | Harries Hawks Optimisation |
| IoT | = | Internet of Things |
| IMWSNs | = | Industrial Multichannel Wireless Sensors Networks |
| ILP | = | Integer Linear Programming |
| IDC | = | Internet Data Centers |
| iCSHS | = | Improved Cuckoo Search and Harmony Search |
| IMPSO | = | Improved Multi-Objective PSO |
| KH | = | Krill Herd Optimisation algorithm |
| LCM | = | Link-aware Clustering Mechanism |
| LP/NLP | = | Linear/Nonlinear Programming |
| LBCP | = | Load-Balanced Clustering Problem |
| LBMPSO | = | Load Balancing technique by Modified PSO |
| LD2FA-PSO | = | Learning Dynamic Deterministic Finite Automata with PSO |
| LB-BC | = | Load Balancing based on Bayes and Clustering |
| MAC | = | Medium Access Control |
| MCS | = | Multi-Candidate Selection |
| MCOP | = | Multi-Criterion Optimisation |
| MANFIS | = | Modified Adaptive Neuro Fuzzy Inference System |
| OABC | = | Optimized Artificial Bee Colony |
| OWSNs | = | Optical-Wireless Sensor Networks |
| PSO | = | Particle Swarm Optimisation |
| PEFT | = | Predict Earliest Finish Time |
| PIO | = | Pigeon inspired Optimisation |
| RMASE | = | Routing Modeling Application Simulation Environment |
| SDN | = | Software-Defined Networking |
| SA | = | Simulated Annealing |
| SALB | = | Self-Acting Load Balancing |
| SIF | = | Swarm Intelligence based Fuzzy |
| SRPMA | = | Secure Routing Protocol based on Multi-objective Ant-colony-optimisation |
| SDMSs | = | Software-Defined Mobile Sinks |
| SFO | = | Sailfish Optimizer |
| TBSLBPSO | = | Task-based System Load Balancing method using PSO |
| T-S | = | Takagi – Sugeno |
| QoS | = | Quality of Service |
| WSN | = | Wireless Sensor Network |